{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "40b3f535-76bc-41e6-bba4-50fd3d2475c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:00.379714Z",
     "iopub.status.busy": "2022-06-14T13:14:00.379241Z",
     "iopub.status.idle": "2022-06-14T13:14:01.352486Z",
     "shell.execute_reply": "2022-06-14T13:14:01.351575Z",
     "shell.execute_reply.started": "2022-06-14T13:14:00.379644Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 导入包\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import font_manager"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8302734-843b-4716-b7ab-3b3559fe7a1c",
   "metadata": {},
   "source": [
    "Matplotlib没有专门的分组绘制api，可以通过循环调用plt.bar函数来实现分组绘制的效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "af5b3c38-5651-4e8f-9c93-443978add709",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:04.090326Z",
     "iopub.status.busy": "2022-06-14T13:14:04.089867Z",
     "iopub.status.idle": "2022-06-14T13:14:04.093878Z",
     "shell.execute_reply": "2022-06-14T13:14:04.093051Z",
     "shell.execute_reply.started": "2022-06-14T13:14:04.090301Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 创建字体管理对象，指向具体的字体文件\n",
    "font = font_manager.FontProperties(\n",
    "    fname=\"/System/Library/Fonts/STHeiti Light.ttc\", size=14, weight=4\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a4239c77-0f5a-42c5-947c-a0fe1125e1bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:05.063586Z",
     "iopub.status.busy": "2022-06-14T13:14:05.063243Z",
     "iopub.status.idle": "2022-06-14T13:14:05.076573Z",
     "shell.execute_reply": "2022-06-14T13:14:05.075895Z",
     "shell.execute_reply.started": "2022-06-14T13:14:05.063562Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'长津湖之水门桥': [2.01, 4.59, 7.99, 11.83, 16],\n",
       " '这个杀手不太冷静': [3.19, 5.08, 6.73, 8.1, 9.35],\n",
       " '奇迹.笨小孩': [5.07, 6.92, 9.3, 11.29, 13.03],\n",
       " '穿过寒冬拥抱你': [2.72, 3.79, 4.45, 4.83, 5.11],\n",
       " '狙击手': [0.56, 0.74, 0.83, 0.88, 0.92],\n",
       " '四海': [0.66, 0.95, 1.1, 1.17, 1.23],\n",
       " '误杀2': [1.13, 1.96, 2.73, 3.42, 4.05]}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 创建实验数据\n",
    "movies = {\n",
    "    \"长津湖之水门桥\": [2.01, 4.59, 7.99, 11.83, 16],\n",
    "    \"这个杀手不太冷静\": [3.19, 5.08, 6.73, 8.1, 9.35],\n",
    "    \"奇迹.笨小孩\": [5.07, 6.92, 9.3, 11.29, 13.03],\n",
    "    \"穿过寒冬拥抱你\": [2.72, 3.79, 4.45, 4.83, 5.11],\n",
    "    \"狙击手\": [0.56, 0.74, 0.83, 0.88, 0.92],\n",
    "    \"四海\": [0.66, 0.95, 1.1, 1.17, 1.23],\n",
    "    \"误杀2\": [1.13, 1.96, 2.73, 3.42, 4.05],\n",
    "}\n",
    "movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a01c6686-9f69-4e12-9a87-ef4a38402e79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:06.767434Z",
     "iopub.status.busy": "2022-06-14T13:14:06.766874Z",
     "iopub.status.idle": "2022-06-14T13:14:06.781038Z",
     "shell.execute_reply": "2022-06-14T13:14:06.780419Z",
     "shell.execute_reply.started": "2022-06-14T13:14:06.767408Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>长津湖之水门桥</th>\n",
       "      <th>这个杀手不太冷静</th>\n",
       "      <th>奇迹.笨小孩</th>\n",
       "      <th>穿过寒冬拥抱你</th>\n",
       "      <th>狙击手</th>\n",
       "      <th>四海</th>\n",
       "      <th>误杀2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.01</td>\n",
       "      <td>3.19</td>\n",
       "      <td>5.07</td>\n",
       "      <td>2.72</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.66</td>\n",
       "      <td>1.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.59</td>\n",
       "      <td>5.08</td>\n",
       "      <td>6.92</td>\n",
       "      <td>3.79</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.99</td>\n",
       "      <td>6.73</td>\n",
       "      <td>9.30</td>\n",
       "      <td>4.45</td>\n",
       "      <td>0.83</td>\n",
       "      <td>1.10</td>\n",
       "      <td>2.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.83</td>\n",
       "      <td>8.10</td>\n",
       "      <td>11.29</td>\n",
       "      <td>4.83</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1.17</td>\n",
       "      <td>3.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16.00</td>\n",
       "      <td>9.35</td>\n",
       "      <td>13.03</td>\n",
       "      <td>5.11</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.23</td>\n",
       "      <td>4.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   长津湖之水门桥  这个杀手不太冷静  奇迹.笨小孩  穿过寒冬拥抱你   狙击手    四海   误杀2\n",
       "0     2.01      3.19    5.07     2.72  0.56  0.66  1.13\n",
       "1     4.59      5.08    6.92     3.79  0.74  0.95  1.96\n",
       "2     7.99      6.73    9.30     4.45  0.83  1.10  2.73\n",
       "3    11.83      8.10   11.29     4.83  0.88  1.17  3.42\n",
       "4    16.00      9.35   13.03     5.11  0.92  1.23  4.05"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 转换成DataFrame，方便操作\n",
    "movieData = pd.DataFrame(movies)\n",
    "movieData"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37a6df3a-ab3b-42a2-9f0d-36198638a65d",
   "metadata": {},
   "source": [
    "## 实现一"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9711fa0b-1066-4cc7-aa11-a2897cc08814",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:08.215638Z",
     "iopub.status.busy": "2022-06-14T13:14:08.215076Z",
     "iopub.status.idle": "2022-06-14T13:14:08.437399Z",
     "shell.execute_reply": "2022-06-14T13:14:08.436630Z",
     "shell.execute_reply.started": "2022-06-14T13:14:08.215613Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置画板\n",
    "plt.figure(figsize=(15, 5), dpi=120)\n",
    "# 设定x轴刻度的绘制坐标\n",
    "xticks = np.arange(len(movies))\n",
    "# 设定柱面宽度\n",
    "barWidth = 0.15\n",
    "# 循环获取每天数据进行绘制\n",
    "i = 2\n",
    "for index in movieData.index:\n",
    "    # 获取一天的数据\n",
    "    oneDay = movieData.iloc[index]\n",
    "    # 绘制该天的全部票房数据\n",
    "    plt.bar(\n",
    "        xticks - i * barWidth, oneDay, width=barWidth, label=\"第{}天票房\".format(index + 1)\n",
    "    )\n",
    "    i -= 1\n",
    "plt.xticks(xticks, movieData.columns, font_properties=font)\n",
    "# 设定图例绘制\n",
    "plt.legend(prop=font)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8d8a4d2-5a19-4375-89e5-3e5591c3cc76",
   "metadata": {},
   "source": [
    "## 实现二"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3fd6e6c5-b2b5-4f3f-b509-36b889417768",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-14T13:14:11.418731Z",
     "iopub.status.busy": "2022-06-14T13:14:11.418398Z",
     "iopub.status.idle": "2022-06-14T13:14:11.633167Z",
     "shell.execute_reply": "2022-06-14T13:14:11.632344Z",
     "shell.execute_reply.started": "2022-06-14T13:14:11.418705Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置画板\n",
    "plt.figure(figsize=(15, 5), dpi=120)\n",
    "# 设定x轴刻度的绘制坐标\n",
    "xticks = np.arange(len(movies))\n",
    "# 设定柱面宽度\n",
    "barWidth = 0.15\n",
    "# 循环获取每天数据进行绘制\n",
    "for index in movieData.index:\n",
    "    # 获取一天的数据\n",
    "    oneDay = movieData.iloc[index]\n",
    "    # 绘制该天的全部票房数据\n",
    "    plt.bar(\n",
    "        xticks - (2 - index) * barWidth,\n",
    "        oneDay,\n",
    "        width=barWidth,\n",
    "        label=\"第{}天票房\".format(index + 1),\n",
    "    )\n",
    "plt.xticks(xticks, movieData.columns, font_properties=font)\n",
    "# 设定图例绘制\n",
    "plt.legend(prop=font)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
